جستجوی استاد راهنمای دانشگاهی

Michael Carbin is the Jamieson Career Development Assistant Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT) and leads the MIT Programming Systems Group. His research focuses on programming systems that address system uncertainty to enhance performance, energy efficiency, and resilience, particularly in environments involving neural networks , approximate computing , and unreliable hardware . His work spans probabilistic programming , quantum computing , and machine learning systems . Articles highlight contributions in pruning neural networks , quantum data structures , and compiler optimization , reflecting trends in deep learning , formal verification , and language-driven systems . Scientific Awards : MIT Frank E. Perkins Award (2020) Sloan Research Fellowship (2020) Facebook Research Award (2019) NSF CAREER Award (2018) Best Paper Awards at OOPSLA (2013, 2014) He has advised numerous graduate students and postdocs including Eric Atkinson, Cambridge Yang, and Charles Yuan, and served on program committees for conferences like POPL, OOPSLA, and ICLR. His group collaborates with institutions such as MIT CSAIL and explores applications in quantum algorithms and probabilistic inference .

• Programming Systems
• Approximate Computing
• Probabilistic Programming
• +۴ مورد دیگر

Prof. Dr.-Ing. Hakan Kayal serves as University Professor for Aerospace Engineering at the University of Würzburg, holding the Chair of Computer Science VIII (Space Technology) and chairing the Interdisciplinary Research Center for Extraterrestrial Studies (IFEX). His leadership bridges computer science and space systems engineering within the university's Institute of Computer Science. Research focuses on three synergistic domains: nanosatellite development for extraterrestrial missions (including the SONATE-2 6U platform demonstrating AI-driven onboard processing), scientific investigation of Unidentified Anomalous Phenomena (UAP) through the university's collaboration with the Federal Aviation Office, and spacecraft autonomy systems enabling higher mission independence. Current projects include the NEAlight mission (extended to develop the Apophis Interceptor concept for the 2029 asteroid flyby), VaMEx3-MarsSymphony for Mars exploration, and JMU Space Observatory initiatives. Publication trends reveal strong emphasis on asteroid defense strategies (particularly for Apophis), CubeSat-based UAP detection methodologies, and real-time AI processing in constrained space environments. His team actively engages students through ADS-B tracking, Meteosat App development, and Moon Base 2030 projects, while recent recognition includes co-authoring a landmark UAP review in Progress in Aerospace Sciences with 33 international scientists.

• Nanosatellites
• Space Systems
• Extraterrestrial Missions
• +۳ مورد دیگر

Veronika Eyring serves as Head of the Earth System Model Evaluation and Analysis Department at the German Aerospace Center (DLR) Institute of Atmospheric Physics and Professor of Climate Modelling at the University of Bremen. She holds dual appointments at these leading institutions, directing cutting-edge research at the intersection of climate science and artificial intelligence. Education: 2008: Habilitation in Environmental Physics at the University of Bremen 1999: PhD in Physics from the University of Bremen 1994: Diploma in Physics from the University of Erlangen Professor Eyring's research program focuses on improving climate models and projections through innovative integration of machine learning techniques and spaceborne Earth observations. Her work spans process-oriented modeling, development of observationally-based performance metrics, and understanding systematic biases in climate models. She has pioneered approaches to weighting model projections based on their performance using machine learning, significantly advancing the field of climate model evaluation. Her research has critical applications across multiple sectors including aeronautics, space research, transportation, and energy systems. Analysis of her recent publications reveals a clear trajectory toward deeper integration of machine learning with traditional climate modeling approaches. Her work has increasingly focused on developing community tools like the Earth System Model Evaluation Tool (ESMValTool) and leading major international initiatives such as the USMILE project (Understanding and Modelling the Earth System with Machine Learning). The publications span climate science, machine learning, Earth system modeling, and remote sensing, with specific emphasis on climate model evaluation, parameterization techniques, and improved climate projections. Scientific Awards: AGU Ambassador Award (2024) TUM Distinguished Affiliated Professor (2024) Gottfried Wilhelm Leibniz Prize (2021) ERC Synergy Grant (2019) Thomson Reuters Highly Cited Researcher (2016-2021) Top female researchers award, Helmholtz-Society (2015) Professor Eyring actively supervises a large research group comprising PhD students working on ML-based sea ice parameterizations, causal model evaluation for air-sea interactions, and machine learning-based detection of droughts in climate projections. She leads the prestigious ERC Synergy Grant USMILE and secured significant funding through the DFG Gottfried Wilhelm Leibniz Prize. Her research group at DLR includes multiple postdocs, research scientists, and software engineers working collaboratively on climate informatics projects. Professor Eyring leads the Earth System Model Evaluation and Analysis Department at DLR, which encompasses research groups focused on CMIP model evaluation, ESMValTool development, and machine learning applications in climate science. She founded and supervises the 'Climate Informatics' Group at the DLR Institute for Data Science in Jena. Her department maintains strong international collaborations, particularly with the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, where she serves as an Affiliate Scientist.

• Climate science
• Climate modelling
• Machine learning for climate models
• +۷ مورد دیگر

Anders Rantzer is a Professor of Automatic Control at the Department of Control Engineering, Faculty of Engineering, Lund University, Sweden. He has held visiting positions at Caltech (2004–2005) and the University of Minnesota (2015–2016) as the Taylor Family Distinguished Visiting Professor. His academic journey began with a PhD from KTH Stockholm in 1991, followed by a postdoc at the Institute for Mathematics and its Applications (IMA), University of Minnesota. His research interests center on modeling, analysis, and synthesis of control systems , with a strong focus on scalability, adaptation, and applications in energy networks . He is particularly known for foundational work in positive systems and integral quadratic constraints (IQCs) . These theoretical frameworks are critical in analyzing stability and robustness of large-scale interconnected systems. His work bridges mathematical rigor with practical engineering applications, especially in sustainable energy and networked systems. The recent publications and lecture materials reflect a consistent trajectory in scalable and robust control, optimization, and distributed systems. Themes such as large-scale convex optimization , nonlinear and stochastic control , and network dynamics dominate his scholarly output, indicating a sustained commitment to advancing control theory for complex, real-world systems. Scientific honors include: Fellow of IEEE Member of the Royal Swedish Academy of Engineering Sciences (IVA) Chairman of the Swedish Scientific Council for Natural and Engineering Sciences Chairman of the Royal Physiographic Society of Lund Rantzer has supervised numerous students and contributed extensively to academic leadership and education. He has been involved in major national and international research initiatives such as WASP (Wallenberg AI, Autonomous Systems and Software Program) and ELLIIT. His work includes developing educational tools and courses in control, optimization, and machine learning. He leads and contributes to research projects on autonomous systems, cloud control, and smart energy networks. He is affiliated with the Control Lab at LTH and participates in collaborative efforts such as the Nordic University Hub on Industrial Internet of Things (HI2OT). His work integrates theoretical advances with practical implementations in robotics, biomedical systems, and industrial automation.

• Control Systems Theory
• Scalable Control
• Adaptive Control
• +۷ مورد دیگر

Prof. Dr. Dominik Schwarz is a faculty member at the Faculty of Physics , Bielefeld University. His research focuses on Cosmology and Particle Physics , particularly in the areas of Dark Energy , Dark Matter , Cosmological Inflation , and Large-Scale Structure Formation . He contributes to projects like the International LOFAR Telescope Consortium and the SFB-TRR 211 on strongly interacting matter. APART Fellow of Austrian Academy of Sciences Humboldt Fellow CERN Fellow His recent work explores the cosmic dipole anisotropy , axion density perturbations , and multi-wavelength cosmic web mapping . He also advances data science infrastructure through the PUNCH4NFDI consortium.

• Cosmology
• Particle Physics
• Astrophysics
• +۶ مورد دیگر

Ulrik Schroeder is a Universitätsprofessor (Full Professor) at RWTH Aachen University, leading the Chair of Learning Technologies within the Faculty of Computer Science. His research focuses on the intersection of educational technology, learning analytics, and immersive technologies with particular emphasis on practical implementations in higher education settings. Professor Schroeder's research spans multiple interconnected domains in educational technology. His primary interests include Learning Analytics implementation (particularly using xAPI standards), Virtual Reality applications for education, Open Educational Resources development and conversion, and gamification approaches for programming education. He has developed several notable tools including convOERter for OER conversion, WebWriter for creating explorable explanations, and various xAPI-based learning analytics infrastructures. His work consistently bridges theoretical frameworks with practical educational applications, often focusing on computer science education contexts. Analysis of his recent publications reveals a strong trend toward integrating Learning Analytics with immersive technologies, particularly Virtual Reality environments. His research demonstrates a systematic approach to educational technology development, with emphasis on scalability, interoperability through standards like xAPI, and practical implementation in real educational settings. The work increasingly focuses on personalized learning paths, quality assurance for educational resources, and privacy-conscious data collection. Co-editor of 21. Fachtagung Bildungstechnologien (DELFI) (2023) Co-editor of Hochschuldidaktik der Informatik HDI 2018 Co-editor of DeLFI 2018 conference proceedings Professor Schroeder has supervised numerous doctoral and postdoctoral researchers who frequently appear as co-authors on his publications, indicating an active research group. His projects often involve interdisciplinary collaborations across computer science, education, and psychology. Current major initiatives include the AIStudyBuddy project for study path analysis and the development of VR classroom simulations for teacher training. His research group, the Learning Technologies Innovation Lab, develops open research tools that support various aspects of educational technology research and implementation.

• Learning Analytics
• Educational Technology
• Virtual Reality Education
• +۵ مورد دیگر

Krishna Gummadi is a Scientific Director and Professor at the Max Planck Institute for Software Systems (MPI-SWS) in Germany, where he leads the Networked Systems Research Group. He also holds a professorship at the University of Saarland, demonstrating his dual commitment to research and academic instruction in computer science. His educational background includes: Ph.D. in Computer Science and Engineering from the University of Washington (2005) B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Madras (2000) Gummadi's research spans networked and distributed computer systems with a current focus on social computing systems. His work addresses critical challenges in algorithmic fairness, privacy in social media, trustworthiness of online identities, and information dissemination in social networks. He approaches these problems through interdisciplinary methods combining user-centric studies, data-centric analysis, and systems-centric design to create practical solutions that enhance fairness, transparency, and user control in online platforms. His methodology integrates large-scale observational studies, computational modeling, and system implementation to tackle complex human-computer interaction challenges at societal scale. His recent publications reveal a strong emphasis on fairness in algorithmic decision making, with significant contributions to quantifying and addressing discrimination in machine learning systems. His work bridges computer science, social science, and ethics, creating frameworks for fair classification, understanding media bias, and developing privacy-preserving techniques that maintain functionality while protecting user data. The research demonstrates a progression from technical system design to addressing societal implications of computing systems. Among his notable scientific achievements: ERC Advanced Grant in 2017 for 'Foundations for Fair Social Computing' Test of Time Awards at ACM SIGCOMM and AAAI ICWSM Casper Bowden Privacy Enhancing Technologies (PET) and CNIL-INRIA Privacy Runners-Up Awards IW3C2 WWW Best Paper Honorable Mention Multiple Best Paper awards across prestigious conferences Gummadi has advised numerous PhD students and postdoctoral researchers who have gone on to prominent positions in academia and industry. His ERC Advanced Grant has supported extensive research into fair social computing, while his leadership in major conferences (including serving as General Chair for ICWSM 2016 and Program Chair for WWW 2015) has shaped research directions in the field. His teaching portfolio includes courses on Distributed Systems, Human-Centered Machine Learning, and Social Media Analysis. He leads the Networked Systems Research Group at MPI-SWS, which has developed several publicly available systems including tools for fair classification, privacy risk assessment, trust evaluation in social media, and information diet management. The group's work bridges theoretical advances with practical implementations that address real-world challenges in social computing, with numerous software releases and datasets made available to the research community.

• Networked Systems
• Distributed Systems
• Social Computing
• +۵ مورد دیگر

Oliver Hohlfeld is a Professor at the University of Kassel, where he leads the Distributed Systems group. He previously held academic positions at Brandenburg University of Technology and RWTH Aachen University, and was a visiting scholar at the University of Wisconsin–Madison. His research focuses on network security, Internet measurements, and Quality of Experience (QoE). He completed his Ph.D. in Computer Science at TU Berlin under Anja Feldmann and holds a B.Sc. and M.Sc. from Darmstadt University of Technology. He also worked at Fraunhofer IGD on telemedical network architectures. His research adopts a data-driven approach, combining large-scale Internet measurements, user studies, and machine learning to understand and improve Internet performance and security. Key areas include DDoS detection, QUIC, HTTP/2, TLS deployment, and BGP analysis. He investigates how protocols like QUIC and HTTP/2 impact user experience and network efficiency, often through empirical studies of real-world deployments. His recent publications highlight a strong trend in network security and protocol analysis, with significant work on DDoS attacks, traffic ingress detection, and web consolidation. He also explores social media dynamics and censorship circumvention through user reviews. 2022 IETF/IRTF Applied Networking Research Prize Best of CCR (2021) for TLS 1.3 deployment study ACM Senior Member (2020) IEEE QoMEX 2019 Best Reviewer Award ACM IMC Community Contribution Award (2018) He has advised numerous Master’s and Bachelor’s students, primarily at RWTH Aachen, and has been a principal investigator in major projects such as AIDOS (AI-based DDoS mitigation), DFG SFB MAKI, COMTEX, and the EU-funded SSICLOPS. He actively serves on the technical program committees of top-tier conferences including SIGCOMM, NSDI, IMC, and CoNEXT, and is a frequent reviewer for leading journals in networking and systems. He leads the Distributed Systems group at the University of Kassel, which conducts research on Internet observability, secure infrastructures, and scalable networking solutions.

• Network Security
• Network Measurements
• Internet Architecture
• +۹ مورد دیگر

Dominique Devriese is a professor at the Department of Computer Science, KU Leuven, and a member of the DistriNet research group. His work bridges computer security, programming languages, and formal verification. Research interests: Functional Programming, Object Capabilities, Secure Compilation, Dependently-typed Programming, Modal Type Theory Teaching: Formal Systems, Object-Oriented Programming, CyberSecurity, Secure Software His research focuses on rigorous software systems security through capability machines and secure compilation techniques. He actively contributes to formal verification using Agda and Haskell, with recent work on multimode type theory and effect parametricity. Key publication trends include: multimode/presheaf type theory, capability-based security models, formal verification of hardware/software abstractions, and parametricity applications in programming languages. Contact: Email: dominique.devriese@kuleuven.be ORCID: 0000-0002-3862-6856

• Functional Programming
• Object Capabilities
• Secure Compilation
• +۵ مورد دیگر

Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections

• Boundary Layer Meteorology
• Atmospheric Turbulence
• GNSS Applications
• +۳ مورد دیگر

Prof. Dr. Erik Rodner is a faculty member at the University of Applied Sciences Berlin (HTW Berlin), where he serves as a Professor for Machine Learning and Data Science. He also contributes to the School of Engineering Sciences - Technology and Life. His research spans computer vision, machine learning, and biomedical applications, with a focus on learning with limited data, robust visual recognition models, and medical image analysis. He has developed innovative methods for medical diagnostics, industrial classification, and anomaly detection. Recent publications (2025-2016) highlight his expertise in visual in-context learning, semi-weakly segmentation, and active learning frameworks. He has collaborated with institutions such as ZEISS Group, Friedrich Schiller University Jena, and UC Berkeley. Scientific Awards: Award for Excellent Teaching (2023)

• Machine Learning
• Computer Vision
• Data Science
• +۵ مورد دیگر

Prof. Dr.-Ing. Annette Eicker is a Professor of Geodesy and Adjustment Calculations at the HafenCity University Hamburg (HCU), where she has been serving since 2016. Prior to her current position, she was an Academic Councillor at the Institute of Geodesy and Geoinformation at the University of Bonn (2014-2016), and has held visiting research positions at NASA's Jet Propulsion Laboratory in Pasadena, USA (2015) and the University of Rennes 1 in France (2014). Her research focuses on satellite gravimetry, particularly utilizing GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (Follow-On) mission data to monitor terrestrial water storage, study climate-related mass changes, and develop advanced methods for gravity field recovery. Her work bridges geodesy, hydrology, and climate science, with significant contributions to understanding global water cycle dynamics and developing next-generation gravity missions like MAGIC (Mass-change And Geosciences International Constellation). Analysis of her recent publications reveals a strong emphasis on improving the accuracy and applications of satellite gravity data for hydrological monitoring, with increasing focus on next-generation missions and daily gravity field solutions. Her research spans from fundamental method development (e.g., GROOPS software toolkit) to practical applications for water resource management and climate change monitoring. Prof. Eicker's work demonstrates leadership in the field of satellite gravimetry, with numerous publications in high-impact journals addressing critical challenges in Earth observation and climate monitoring. Though specific awards aren't mentioned in the provided materials, her extensive publication record and leadership in major projects like MAGIC indicate significant recognition within the geodetic and hydrological communities. Her research has strong implications for understanding climate change impacts on water resources, with applications in drought monitoring, flood risk assessment, and sustainable water management. She maintains active collaborations with international institutions including NASA's Jet Propulsion Laboratory and has contributed to major initiatives like the GlobalCDA Project, which integrates geodetic and remote sensing data with hydrological models.

• Geodesy
• Satellite Gravimetry
• Gravity Field Modeling
• +۴ مورد دیگر

Lorenz Dörschel is an Adjunct Professor (Lehrbeauftragter) at the Institute of Automatic Control at RWTH Aachen University. He holds the academic title PD Dr.-Ing. habil, signifying post-doctoral research qualifications. His position is part-time, focusing on advanced control theory and applications. His primary research interests include: Control of distributed parameter systems (e.g., fluid dynamics, thermal processes) Model predictive control for industrial and automotive systems Parameter space methods for robust controller design Model reduction techniques for complex nonlinear systems Dörschel's recent publications (2018-2024) demonstrate broad applications across biomedical engineering, renewable energy, automotive systems, and industrial automation. His work consistently integrates mathematical rigor with practical implementations, emphasizing advanced control methodologies like nonlinear MPC, Lyapunov-based design, and Bayesian optimization. A recurring theme is the development of computationally efficient control strategies for distributed parameter systems. No scientific awards, student advising relationships, or research grants are documented in the available information.

• Control Theory
• Distributed Parameter Systems
• Model Predictive Control
• +۳ مورد دیگر

Christian Hirt is a Senior Research Fellow at Curtin University, Australia, and a Hans Fischer Fellow at the Technical University of Munich (TUM). His academic career includes roles as an Associate Professor at HafenCity University Hamburg and professional contributions at the University of Hanover. He specializes in geodesy, gravity field modeling for Earth, Moon, and Mars, and geodetic astronomy. Hirt has developed advanced systems like the Digital Zenith Camera and contributed to regional geoid models for Australia and New Zealand. His research also addresses atmospheric refraction and high-resolution gravity field analysis using satellite data like GOCE. Notable achievements include attracting $1.25M AUD in research funding and leading an ARC Discovery Project on GOCE satellite gravimetry. Awards include the ARC Discovery Outstanding Researcher Award (2011) and the Victor-Rizkallah Award (2001). Research focuses on gravity field modeling, including planetary topography effects, spectral forward modeling, and validation of global gravity models. Hirt’s work bridges geodetic instrumentation (e.g., QDaedalus systems) with theoretical advancements in forward modeling techniques. His publications span planetary gravity models (Mars, Moon), geoid-quasigeoid corrections, and high-resolution terrain analysis. Grants include a $450K ARC Discovery Project on GOCE applications in Australia. Awards and recognitions highlight his contributions to geodesy and planetary science. His labs and instruments, such as the QDaedalus system, enable precise vertical deflection measurements in challenging terrains. Collaborations include global geoid validation networks and digital elevation model services (IDEMS).

• Geodesy
• Gravity Field Modelling
• Geodetic Astronomy
• +۳ مورد دیگر

Prof. Dr.-Ing. Frank Thielecke is a full Professor and the head of the Institute of Aircraft Systems Engineering (Flugzeug-Systemtechnik) at Technische Universität Hamburg (TUHH), Germany. His research is centered on advanced aircraft systems, avionics, flight control, and the integration of emerging technologies such as hydrogen and hybrid-electric propulsion. Institution: Technische Universität Hamburg Department: Institute of Aircraft Systems Engineering (Flugzeug-Systemtechnik) Email: frank.thielecke@tuhh.de Office: Neßpriel 5, Room 1.012, 21129 Hamburg His research interests include integrated modular avionics (IMA), model-based systems engineering (MBSE), aircraft load estimation, health monitoring, fault diagnosis, and sustainable aviation technologies. He leads a research group actively contributing to next-generation aircraft design, with a strong focus on digitalization, virtual testing, and system safety. The recent publications highlight a consistent trend in developing model-based tools and architectures for avionics and aircraft systems. Key themes include the design of IMA platforms, virtual integration, system validation, hydrogen aircraft systems, and control algorithms for UAVs and flexible aircraft. His work frequently appears in AIAA, DASC, DLRK, and CEAS conferences and journals. Prof. Thielecke has been involved in numerous collaborative research projects focusing on more-electric aircraft, fuel cell systems, and advanced actuation. He has contributed to the development of frameworks such as ASHLEY and SArA for avionics platform design and systems architecting. His team also works on noise reduction in hydraulic systems and condition monitoring for aircraft subsystems. He supervises a group of researchers and PhD students, many of whom co-author his publications. While specific student names are not listed, long-term collaborators like Oliver Luderer, Thimo Bielsky, Nils Külper, and Philipp Chrysalidis are likely doctoral candidates or postdoctoral researchers in his group. He has secured funding for projects related to hydrogen aircraft, hybrid propulsion, and digital avionics engineering. His lab, the Institute of Aircraft Systems Engineering, operates test benches for avionics, hydraulic systems, and flight control validation. The team uses advanced simulation, co-simulation (e.g., FMI), and hardware-in-the-loop techniques for virtual integration and testing. Ongoing work includes the development of tools for early validation of flight control platforms and automated requirement-based testing.

• Aircraft Systems Engineering
• Avionics
• Integrated Modular Avionics (IMA)
• +۱۲ مورد دیگر